Instructions to use Locutusque/OpenCerebrum-2.0-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Locutusque/OpenCerebrum-2.0-7B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Locutusque/OpenCerebrum-2.0-7B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Locutusque/OpenCerebrum-2.0-7B")
model = AutoModelForCausalLM.from_pretrained("Locutusque/OpenCerebrum-2.0-7B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Locutusque/OpenCerebrum-2.0-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Locutusque/OpenCerebrum-2.0-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Locutusque/OpenCerebrum-2.0-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Locutusque/OpenCerebrum-2.0-7B

SGLang

How to use Locutusque/OpenCerebrum-2.0-7B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Locutusque/OpenCerebrum-2.0-7B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Locutusque/OpenCerebrum-2.0-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Locutusque/OpenCerebrum-2.0-7B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Locutusque/OpenCerebrum-2.0-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Locutusque/OpenCerebrum-2.0-7B with Docker Model Runner:
```
docker model run hf.co/Locutusque/OpenCerebrum-2.0-7B
```

Can this model perform Basic arithmetic operations

by Kv-boii - opened Apr 15, 2024

Discussion

Kv-boii

Apr 15, 2024

i'm building a rag model for csv files and i'm choosing models for the generation part that can also perform calculations - like it need to find the value for total sales in year 2023 by calculating the sum of monthly sales which is present in the csv file

Locutusque

Owner Apr 15, 2024

Could you give an example? It really depends how large the arithmetic operation is.

Kv-boii

Apr 17, 2024

Like the model should be able to calculate like this
prompt: "What is the total sales of the year 2023 "
ans: "the total sales is xxxx in year 2023"

but the csv has only monthly sales - so in this case sum , i want to perform sum, subtract, percentage kinda operations
just minimal and basic functionalities is required for now

Locutusque

Owner Apr 19, 2024

I would say it could perform that kind of arithmetic

Locutusque changed discussion status to closed Apr 19, 2024

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